Are you really connected...?
There are certain factors that the marketing teams of these social media (SM) sites put in place to help the user feel more connected to their counterparts on SM. The algorithms that the SM sites employ are one of the things designed to feed the user more of what they like because what they like helps the user feel good and valid in their own opinion this in itself leads to homophily. Homophily as defined by American Psychological Association (2017) “the tendency for individuals who are socially connected in some way to display certain affinities, such as similarities in demographic background, attitudes, values, and so on” (para. 1). Meaning we people will gravitate to other people who look, think, and at like they do. Read more about homophily. https://smartalick1.tumblr.com/
Algorithms and cognitive biases
The use of algorithms by the SM sites has a large effect on cognitive biases and can intensify homophily and contribute to feelings of isolation leading to many problems such as hate speech and political extremism. The algorithms that these sites employ are good at weeding out what the user wants to see and what they like. These algorithms are designed to pick out the most relevant information, the things that cause real engagement in the user. Cognitive bias can be grown out of this, Ciampaglia, et al. (2018) “the detailed advertising tools built into many social media platforms let disinformation campaigners exploit confirmation bias by tailoring messages to people who are already inclined to believe them” (para. 14).
The best steps an SM user can take to ensure that they do not get caught in the trap of cognitive biases is to fact check the information that they are seeing. “social media platforms expose users to a less diverse set of sources than do non-social media sites” (Ciampaglia, et al., 2018, p. 15). The user should also make sure that they are gathering information form a variety of different sources to help get the most accurate information possible.
American Psychological Association. (2017). http://www.apa.org/monitor/2017/12/numbers
Ciampaglia,, G. L., Menczer, F., & The Conversation US. (2018, June 21). Scientific American. http://scientificamerican.com/article/biases-make-people-vulnerable-to-misinformation-spread-by-social-media/
